Founding Machine Learning Engineer
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Die Stelle
Lead the end-to-end ML stack for a new global consumer AI product, from data to deployment.
Own model selection, training strategy, evaluation, and scalable inference architectures.
Design and adapt frontier models (LLaMA, Mistral, Qwen, Claude-compatible) and state-of-the-art fine-tuning methods (LoRA/QLoRA, SFT, DPO, distillation).
Build robust data systems for high-quality synthetic and real-world data, plus alignment and guardrails.
Architect low-latency inference pipelines (vLLM, TensorRT-LLM, DeepSpeed) and optimize GPU usage.
Influence early product direction with a founder mindset, solving zero-to-one problems end-to-end.
Own model selection, training strategy, evaluation, and scalable inference architectures.
Design and adapt frontier models (LLaMA, Mistral, Qwen, Claude-compatible) and state-of-the-art fine-tuning methods (LoRA/QLoRA, SFT, DPO, distillation).
Build robust data systems for high-quality synthetic and real-world data, plus alignment and guardrails.
Architect low-latency inference pipelines (vLLM, TensorRT-LLM, DeepSpeed) and optimize GPU usage.
Influence early product direction with a founder mindset, solving zero-to-one problems end-to-end.
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